In clinical trials, placebo response is considered a beneficial effect arising from multiple factors, including the patient’s expectations for the treatment. Due to the presence of placebo response, the classical parallel design often fails to declare an efficacious treatment. The Sequential Parallel Comparison Design (SPCD), a two-stage design where the first stage is a classical parallel trial, followed by another parallel trial among placebo patients from the first stage, was proposed to mitigate the placebo response. In SPCD, in lieu of treatment effect, a weighted average of the mean treatment difference in Stage I among all randomized patients and the mean treatment difference in Stage II among placebo non-responders was proposed as the efficacy measure. However, by mixing two possibly different populations, this weighted average lacks interpretability, the choice of weight remains controversial, and the classification of patients into placebo responders and non-responders via hard criterion-based rule warrants careful consideration. In this work, we first elaborate and study the shortcomings surrounding this efficacy measure, which motivates us to propose causal estimands for clinically meaningful principal strata under the principal stratification framework. To make the estimands identifiable, we invoke a set of assumptions and introduce two sensitivity parameters. Meanwhile, in the absence of a clinically proven criterion for classifying responders and non-responders, we additionally suggest estimating the response status and sensitivity parameters via the Expectation-Maximization (EM) algorithm by treating the principal strata as full latent characteristics. Next, we further refine and alternatively propose a more consistent and sophisticated EM procedure for classification, point estimation, and hypothesis testing. Finally, we evaluate our methods with extensive simulation studies and apply them to an actual SPCD study of antidepressant therapy to assess the benefit of low-dose aripiprazole adjunctive to antidepressant therapy treatment, the ADAPT-A trial. In conclusion, we believe this is an important step toward a more rigorous and transparent approach to evaluating the treatment benefit in the presence of placebo response. / 2025-09-18T00:00:00Z
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/46919 |
| Date | 18 September 2023 |
| Creators | Liu, Xiaoyan |
| Contributors | Doros, Gheorghe |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
| Rights | Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/ |
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